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Issue 4, 2014
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Nondestructive determination of bamboo shoots lignification using FT-NIR with efficient variables selection algorithms

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Abstract

To achieve the rapid and nondestructive determination of bamboo shoots lignification associated with crude fiber content and firmness, Fourier transform near infrared (FT-NIR) spectroscopy technique was used in this paper. The identification of efficient spectral variables selection algorithms: backward interval PLS (Bi-PLS), Monte Carlo uninformative variables elimination method (MC-UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithms (GA) were also discussed. The partial least squares (PLS) algorithm was applied to establish prediction models for crude fiber content and firmness after spectral preprocessing and variables selection. The correlation coefficient (R) and root mean square error of prediction (RMSEP) were used to assess predictive effects of PLS models. Modeling results showed that the CARS-GA-PLS model was prime for crude fiber content prediction (R = 0.9508, RMSEP = 0.0598), and the CARS-PLS model was superior for firmness prediction (R = 0.9681, RMSEP = 0.8003). The overall results sufficiently demonstrated that the FT-NIR spectroscopy technique could determine successfully crude fiber content and firmness of postharvest bamboo shoots.

Graphical abstract: Nondestructive determination of bamboo shoots lignification using FT-NIR with efficient variables selection algorithms

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Publication details

The article was received on 11 Oct 2013, accepted on 23 Nov 2013 and first published on 25 Nov 2013


Article type: Paper
DOI: 10.1039/C3AY41777H
Citation: Anal. Methods, 2014,6, 1090-1095
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    Nondestructive determination of bamboo shoots lignification using FT-NIR with efficient variables selection algorithms

    F. Xu, X. Huang, H. Dai, W. Chen, R. Ding and E. Teye, Anal. Methods, 2014, 6, 1090
    DOI: 10.1039/C3AY41777H

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